# EBA Report on Big Data and Advanced Analytics (EBA/REP/2020/01): Report on Big Data and Advanced Analytics

Source: https://www.bankingnewsai.com/ai-regulation/documents/eba-rep-2020-01-big-data-advanced-analytics
Last updated: Aug 26, 2026

The EBA's Report on Big Data and Advanced Analytics (EBA/REP/2020/01), published January 13, 2020, is the EU's foundational statement of what supervisors expect from bank use of machine learning. It sets out four pillars needed to roll out advanced analytics — data management, technological infrastructure, organisation and governance, and analytics methodology — plus a set of 'elements of trust' including ethics, explainability and interpretability, fairness and bias avoidance, traceability and auditability, data protection, consumer protection and security.

## At a glance

| Field | Value |
| --- | --- |
| Authority | [EBA](https://www.bankingnewsai.com/ai-regulation/eba) |
| Type | Report |
| Status | Final |
| Published | Jan 13, 2020 |
| Applies to | EU credit institutions and payment institutions using big data, advanced analytics and machine learning (thematic report, not binding) |
| Official text | https://www.eba.europa.eu/publications-and-media/press-releases/eba-report-identifies-key-challenges-roll-out-big-data-and |

## Key points

- Published January 13, 2020 as EBA/REP/2020/01 after an EBA survey of institutions on BD&AA use.
- Four key pillars for BD&AA roll-out: data management, technological infrastructure, organisation and governance, analytics methodology.
- Elements of trust: ethics, explainability and interpretability, fairness and bias avoidance, traceability and auditability, data protection, consumer protection, security.
- Observes that most reported use cases at the time were in fraud detection, AML, credit scoring and customer engagement, with many still at pilot stage.
- Explicitly framed as supporting technology-neutral regulation and supervision rather than proposing new rules.
- Formed the basis for later EBA work on ML in IRB models (2021–23) and for the AI Act mapping exercise (2025).

## What changed for banks

Before 2020 there was no EU-wide banking-supervisory articulation of expectations for machine learning. This report gave national supervisors and the ECB a common vocabulary — explainability, traceability, bias avoidance — that later reappears in the ML-for-IRB papers, the ECB's model-approval practice, and the EBA's reading of the AI Act. Banks still cite it as the origin of EU 'trustworthy AI in banking' expectations.

## Use cases it governs

- [Model risk management](https://www.bankingnewsai.com/ai-regulation/by-use-case#model-risk)
- [AI governance (general)](https://www.bankingnewsai.com/ai-regulation/by-use-case#governance-general)
- [Credit scoring & underwriting](https://www.bankingnewsai.com/ai-regulation/by-use-case#credit-underwriting)
- [Fraud detection](https://www.bankingnewsai.com/ai-regulation/by-use-case#fraud)
- [AML / KYC](https://www.bankingnewsai.com/ai-regulation/by-use-case#aml-kyc)

## FAQ

### What are the EBA's 'elements of trust' for advanced analytics?

Ethics, explainability and interpretability, fairness and bias avoidance, traceability and auditability, data protection, consumer protection, and security — set out in the EBA's January 2020 Report on Big Data and Advanced Analytics (EBA/REP/2020/01).

### Is the 2020 EBA big data report binding on banks?

No. It is a thematic report describing trends and key considerations, intended to support technology-neutral supervision. It is not guidelines under Article 16 of the EBA Regulation, but supervisors draw on it in dialogue with banks.

## Related documents

- [ESA Statement on ICT risks from frontier AI models (JC 2026 25)](https://www.bankingnewsai.com/ai-regulation/documents/esas-jc-2026-25-frontier-ai-statement) — ESA Statement: Toward a consistent and risk-based approach for ICT risks from frontier AI models (Jul 31, 2026)
- [EBA factsheet: AI Act implications for the EU banking and payments sector](https://www.bankingnewsai.com/ai-regulation/documents/eba-ai-act-factsheet-2025) — AI Act: implications for the EU banking and payments sector (Nov 21, 2025)
- [EBA Chair letter to the Commission on the AI Act mapping exercise (EBA/2025/D/5384)](https://www.bankingnewsai.com/ai-regulation/documents/eba-2025-d-5384-ai-act-mapping-letter) — Outcome of EBA's AI Act mapping exercise — letter to DG FISMA and DG CNECT (Nov 21, 2025)
- [EBA Work Programme 2026](https://www.bankingnewsai.com/ai-regulation/documents/eba-work-programme-2026) — EBA Work Programme 2026 — AI Act implementation and digital-finance priorities (Oct 1, 2025)
- [EBA report: Rising application of AI in EU banking and payments (Sep 2025)](https://www.bankingnewsai.com/ai-regulation/documents/eba-ai-adoption-report-2025) — Rising application of AI in EU banking and payments sector (Sep 25, 2025)
- [EBA follow-up report on machine learning for IRB models (EBA/REP/2023/28)](https://www.bankingnewsai.com/ai-regulation/documents/eba-rep-2023-28-ml-irb-follow-up) — Machine Learning for IRB Models — Follow-up report from the consultation on the Discussion paper on machine learning for IRB models (Aug 4, 2023)
- [EBA/GL/2022/15 (remote customer onboarding)](https://www.bankingnewsai.com/ai-regulation/documents/eba-gl-2022-15-remote-customer-onboarding) — EBA/GL/2022/15 Guidelines on the use of Remote Customer Onboarding Solutions under Article 13(1) of Directive (EU) 2015/849 (Nov 22, 2022)
- [EBA discussion paper on machine learning for IRB models](https://www.bankingnewsai.com/ai-regulation/documents/eba-ml-irb-discussion-paper-2021) — Discussion Paper on machine learning for IRB models (Nov 11, 2021)

Last reviewed Aug 26, 2026. Cite the official text (https://www.eba.europa.eu/publications-and-media/press-releases/eba-report-identifies-key-challenges-roll-out-big-data-and) for the rule and this page for the summary and dates.

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